基于混合遗传退火算法的并行测试任务调度优化

并行测试任务的优化调度是并行测试技术的核心问题之一。可以充分利用混合遗传退火算法优异的全局最优搜索能力来寻找具有最大并行率的并行任务序列。首先,建立了并行测试任务调度问题的数学模型;给出了并行率的定义,设计了一种满足资源约束与任务时序约束的基因编码方法及相应的遗传退火操作方案。最后,对实例进行仿真实验,结果验证了该算法的有效性及优越性。

Optimization for the Parallel Test Task Scheduling Based on hybrid GASA

The optimized parallel test tasks scheduling is a key problem to the parallel test. The hybrid GASA can be used to find the parallel test tasks arrange of the maxim parallel efficiency, for it has an excellent ability in searching for the globally optimal solution. The mathematical model of the problem and the definition of parallel efficiency are put forward. The gene coding and the hybrid GASA operating methods which could satisfy both the resource constrains and task sequence restriction are introduced. The result of simulation shows that the algorithm is feasible and efficient.